Perencanaan Sistem Instalasi Plambing Air Bersih dan Air Limbah di Apartemen Menara Cibinong Tower C
Bibliographic record
Abstract
The high population growth demands the need for housing, so apartments are considered as a solution in meeting the need for housing. Basically, every business or development activity has an impact on the environment, both positive and negative. Plumbing systems for clean water, waste water and ventilation in buildings can reduce the possibility of environmental pollution and health problems. This study aims to meet the needs of clean water and maintain the sanitation health of building occupants. The reference method is SNI 7065-2005 for calculating the need for clean water and SNI 8153-2015 for determining the dimensions of clean water pipes. The calculation results the population in the Cibinong Tower C apartment building is 957 people with a total need for clean water of 87.95 m3/ day. In meeting the daily needs of clean water in the planning building, a ground water tank with a capacity of 120 m3 is used and a roof tank is used to fulfill water needs at certain hours with a capacity of 49 m3. To distribute water from GWT to RT using a pump with a power capacity of 33.44 Kwatt. The diameter of the clean water pipe uses dimensions from 20 mm to 125 mm. For blackwater wastewater using pipes with dimensions of 60 mm–140 mm and for greywater wastewater using pipes with dimensions of 32 mm–114 mm, while for ventpipes using pipe dimensions of 42 mm–114 mm
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".